Multi-agent Reinforcement Learning

The target of Multi-agent Reinforcement Learning is to solve complex problems by integrating multiple agents that focus on different sub-tasks. In general, there are two types of multi-agent systems: independent and cooperative systems.

Source: Show, Describe and Conclude: On Exploiting the Structure Information of Chest X-Ray Reports

Papers

Recently Added Most Hyped Most Active Needs Verification Most Verified

Showing 111–120 of 1718 papers

Title	Date	Tasks	Status	Hype
Decentralized Social Navigation with Non-Cooperative Robots via Bi-Level Optimization	Jun 15, 2023	Collision AvoidanceMulti-agent Reinforcement Learning	CodeCode Available	1
A Versatile Multi-Agent Reinforcement Learning Benchmark for Inventory Management	Jun 13, 2023	Autonomous DrivingManagement	CodeCode Available	1
iPLAN: Intent-Aware Planning in Heterogeneous Traffic via Distributed Multi-Agent Reinforcement Learning	Jun 9, 2023	Autonomous VehiclesCollision Avoidance	CodeCode Available	1
Progression Cognition Reinforcement Learning with Prioritized Experience for Multi-Vehicle Pursuit	Jun 8, 2023	Multi-agent Reinforcement Learningreinforcement-learning	CodeCode Available	1
MA2CL:Masked Attentive Contrastive Learning for Multi-Agent Reinforcement Learning	Jun 3, 2023	Contrastive LearningMulti-agent Reinforcement Learning	CodeCode Available	1
Model-aided Federated Reinforcement Learning for Multi-UAV Trajectory Planning in IoT Networks	Jun 3, 2023	Federated LearningMulti-agent Reinforcement Learning	CodeCode Available	1
Is Centralized Training with Decentralized Execution Framework Centralized Enough for MARL?	May 27, 2023	Multi-agent Reinforcement Learningreinforcement-learning	CodeCode Available	1
An Empirical Study on Google Research Football Multi-agent Scenarios	May 16, 2023	BenchmarkingMulti-agent Reinforcement Learning	CodeCode Available	1
Robust multi-agent coordination via evolutionary generation of auxiliary adversarial attackers	May 10, 2023	DiversityMulti-agent Reinforcement Learning	CodeCode Available	1
SMAClite: A Lightweight Environment for Multi-Agent Reinforcement Learning	May 9, 2023	Multi-agent Reinforcement Learningreinforcement-learning	CodeCode Available	1

Show:10 25 50

← PrevPage 12 of 172Next →

All datasets ParticleEnvs Cooperative Communication SMAC-Exp UAV Logistics

Benchmark Results

#	Model	Metric	Claimed	Verified	Status
1	MATD3	final agent reward	-14	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	DRIMA	Median Win Rate	15	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	Fusion-Multi-Actor-Attention-Critic	Average Reward	39	—	Unverified